Association between hemoglobin glycation index and 5-year major adverse cardiovascular events: the REACTION cohort study

The relationship between hemoglobin glycation index and all-cause mortality in ill critically patients with heart failure: a retrospective study in MIMIC-IV database

BACKGROUND

Heart failure (HF) is a major cause of mortality in critically ill patients and often requires intensive care. The hemoglobin glycation index (HGI), defined as the difference between predicted glycated hemoglobin (HbA1c) and measured HbA1c, may provide additional prognostic insights beyond traditional glycemic metrics.

METHODS

We conducted a retrospective analysis of 8,098 adult patients with HF from the MIMIC-IV database (2008-2022). All were first-time ICU admissions with available hematologic and metabolic data. Patients were stratified into three groups (T1 ≤ - 1.26, - 1.26 < T2 < 1.74, T3 ≥ 1.74) based on HGI. Baseline characteristics were recorded within 24 h of ICU admission, including demographic data, disease severity scores, comorbidities, and medication use. Logistic regression and Cox proportional hazards models assessed the associations between HGI and in-hospital, 30-day, and 1-year all-cause mortality, adjusting for age, sex, race, comorbidities, laboratory results, and relevant treatments. Restricted cubic spline (RCS) analysis was performed to examine potential non-linear relationships. We used sensitivity analyses to increase the confidence in our primary outcome.

RESULTS

Patients in the lowest HGI group (T1) had significantly higher in-hospital, 30-day, and 1-year mortality than those in the other two groups. Specifically, T1 showed an 18.6% in-hospital mortality rate, compared with 12.3% and 9.7% in T2 and T3, respectively (p < 0.001). Fully adjusted models revealed that each 1-unit increase in HGI was associated with an approximate 12% reduction in in-hospital mortality risk (OR = 0.88; 95%CI: 0.83-0.93), and an 3% decreased risk of 1-year all-cause mortality (HR 0.97; 95%CI0.94~1.00). RCS analysis indicated a J-shaped relationship between HGI and mortality, underscoring the heightened risk associated with very low HGI. We conducted sensitivity analyses by separately excluding missing data, diagnosed sepsis, and diagnosed hepatic impairment, consistent with the primary analysis.

CONCLUSIONS

In critically ill HF patients, extremely low HGI levels correlate with poorer short- and long-term survival. These findings suggest that HGI could serve as an adjunct risk stratification tool, prompting closer monitoring and potential intervention in patients with markedly low HGI.

Hemoglobin glycation index among adults with type 1 diabetes: Association with double diabetes features

BACKGROUND

The hemoglobin glycation index (HGI) represents the discrepancy between the glucose management indicator (GMI) based on mean blood glucose levels and laboratory values of glycated hemoglobin (HbA1c). The HGI is a promising indicator for identifying individuals with excessive glycosylation, facilitating personalized evaluation and prediction of diabetic complications. However, the factors influencing the HGI in patients with type 1 diabetes (T1D) remain unclear. Autoimmune destruction of pancreatic β cells is central in T1D pathogenesis, yet insulin resistance can also be a feature of patients with T1D and their coexistence is called "double diabetes" (DD). However, knowledge regarding the relationship between DD features and the HGI in T1D is limited.

AIM

To assess the association between the HGI and DD features in adults with T1D.

METHODS

A total of 83 patients with T1D were recruited for this cross-sectional study. Laboratory HbA1c and GMI from continuous glucose monitoring data were collected to calculate the HGI. DD features included a family history of type 2 diabetes, overweight/obesity/central adiposity, hypertension, atherogenic dyslipidemia, an abnormal percentage of body fat (PBF) and/or visceral fat area (VFA) and decreased estimated insulin sensitivity. Skin autofluorescence of advanced glycation end products (SAF-AGEs), diabetic complications, and DD features were assessed, and their association with the HGI was analyzed.

RESULTS

A discrepancy was observed between HbA1c and GMI among patients with T1D and DD. A higher HGI was associated with an increased number of SAF-AGEs and a higher prevalence of diabetic microangiopathy (P = 0.030), particularly retinopathy (P = 0.031). Patients with three or more DD features exhibited an eight-fold increased risk of having a high HGI, compared with those without DD features (adjusted odds ratio = 8.12; 95% confidence interval: 1.52-43.47). Specifically, an elevated PBF and/or VFA and decreased estimated insulin sensitivity were associated with high HGI. Regression analysis identified estimated insulin sensitivity and VFA as factors independently associated with HGI.

CONCLUSION

In patients with T1D, DD features are associated with a higher HGI, which represents a trend toward excessive glycosylation and is associated with a higher prevalence of chronic diabetic complications.

Impact of glycemic control metrics on short- and long-term mortality in transcatheter aortic valve replacement patients: a retrospective cohort study from the MIMIC-IV database

BACKGROUND

Glycemic control is critical for managing transcatheter aortic valve replacement (TAVR) patients, especially those in intensive care units (ICUs). Emerging metrics such as the hemoglobin glycation index (HGI), stress hyperglycemia ratio (SHR), and glycemic variability (GV) offer advanced insights into glucose metabolism. However, their prognostic implications for short- and long-term outcomes post-TAVR remain underexplored.

METHODS

This retrospective cohort study analyzed 3342 ICU-admitted TAVR patients via the MIMIC-IV database. Patients were stratified into tertiles for HGI, SHR, and GV levels. Survival analyses, including Kaplan‒Meier curves, Cox proportional hazards models and restricted cubic splines (RCSs), were used to assess associations between glycemic control metrics and 30-day and 365-day all-cause mortality in these patients. Sensitivity analyses, subgroup assessments, and external validation were also performed to verify the study findings.

RESULTS

During follow-up, 1.6% and 6.9% of patients experienced 30-day and 365-day mortality after TAVR, respectively. In the fully adjusted cox regression model, lower HGI (HR 1.48, 95% CI 1.05-2.09, P = 0.025) and higher SHR (HR 1.63, 95% CI 1.15-2.32, P = 0.006) were most significantly associated with an increased risk of 365-day mortality. Higher SHR was also significantly associated with an increased risk of 30-day mortality in patients (HR 2.92, 95% CI 1.32-6.45, P = 0.008). Both lower (HR 0.59, 95% CI 0.38-0.92, P = 0.019) and higher GV levels (HR 1.43, 95% CI 1.06-1.93, P = 0.020) were associated with the risk of 365-day mortality.

CONCLUSIONS

In critically ill TAVR patients, glycemic control metrics are closely associated with long-term all-cause mortality. The HGI, SHR, and GV provide prognostic insights into clinical outcomes that surpass conventional glucose measurements. These findings highlight the importance of personalized glycemic management strategies in improving TAVR patient outcomes.

Association between the haemoglobin glycation index and 30-day and 365-day mortality in patients with heart failure admitted to the intensive care unit

BACKGROUND

The hemoglobin glycation index (HGI) represents the difference between the observed and predicted values of haemoglobin A1c (HbA1c). However, the association between HGI and prognosis of heart failure (HF) is not completely clarified yet and requires more investigation. This study aimed to explore the connection between HGI and mortality in HF patients.

METHODS

The data for the study were derived from the MIMIC-IV database from 2008 to 2019, a publicly available clinical database in intensive care. A linear regression equation between HbA1c and fasting blood glucose (FBG) was established to calculate predicted HbA1c. The endpoints were 30-day and 365-day all-cause mortality. Kaplan-Meier analysis was utilized to compare survival rates across groups differentiated by their HGI levels. The Cox regression models and restricted cubic spline (RCS) analysis were utilized to analyze the association between HGI and mortality.

RESULTS

The study collected a total of 2846 patients with HF (40.1% male), of whom 305 patients (10.7%) died within 30 days and 954 patients (33.5%) died within 365 days. Kaplan-Meier curves revealed patients with higher HGI had significantly higher mortality risks (log-rank P < 0.001). A high HGI was significantly associated with 30-day mortality (adjusted HR [aHR]: 2.36, 95% CI: 1.74-3.20, P < 0.001) and 365-day mortality (aHR: 1.40, 95% CI: 1.16-1.68, P < 0.001) after adjustment for potential confounders. Likewise, each unit increase in the HGI correlated with a 1.42-fold higher risk of 30-day mortality (aHR: 1.42, 95% CI: 1.28-1.57, P < 0.001) and 1.19-fold higher risk of 365-day mortality (aHR: 1.19, 95% CI: 1.11-1.68, P < 0.001). RCS analysis suggested an L-shaped nonlinear association between HGI and clinical endpoints (P for nonlinearity < 0.001), with an inflection point value of - 1.295. Subgroup analysis and sensitivity analysis revealed that the correlation between HGI and 30-day and 365-day all-cause mortality remained consistent.

CONCLUSIONS

In ICU-admitted HF patients, HGI was independently associated with increased risks of 30-day and 365-day mortality and the identification of high HGI (> 0.709) provided a valuable tool for clinicians to detect high-risk populations. Integrating HGI into routine clinical practice might strengthen the prognosis-based decision making improve HF patient outcomes.

Association between hemoglobin glycation index and adverse outcomes in critically ill patients with myocardial infarction: A retrospective cohort study

BACKGROUND AND AIM

The prognosis of critically ill patients with myocardial infarction (MI) is associated with metabolic disturbances. The hemoglobin glycation index (HGI), a marker of glycemic variability, has been linked to adverse outcomes in critically ill populations. This study aimed to explore the relationship between HGI and adverse outcomes in critically ill MI patients.

METHODS AND RESULTS

This retrospective cohort study used data from the MIMIC-IV database, focusing on critically ill MI patients. Linear regression was applied to model the relationship between glucose and HbA1c, from which HGI values were calculated. Patients were grouped into quartiles based on HGI. Primary outcomes included 30-day, 180-day, and 365-day all-cause mortality. Kaplan-Meier survival analysis, logistic regression, Cox proportional hazards models, and restricted cubic spline (RCS) analysis were employed to assess the relationship between HGI and adverse outcomes. A total of 2480 patients were included. Lower HGI was associated with significantly increased risks of 30-day, 180-day, 365-day, and hospital all-cause mortality. RCS analysis revealed an inverse J-shaped relationship between HGI and mortality risk.

CONCLUSIONS

Low HGI in critically ill MI patients is significantly associated with higher all-cause mortality, highlighting its potential as a prognostic marker for early risk stratification and management optimization.

Association between hemoglobin glycation index and poor outcome after endovascular thrombectomy in acute ischemic stroke

Background

The prognostic significance of hemoglobin glycation index (HGI) on acute ischemic stroke (AIS) patients treated with endovascular thrombectomy (EVT) remained unclear. This study aimed to investigate the association between HGI and the risk of poor outcome after EVT.

Methods

We retrospectively enrolled AIS patients with large vessel occlusion in the anterior circulation treated with EVT from a multicenter study. Poor outcome was defined as a modified Rankin scale score > 2 points at 90 days after EVT. We used multivariable logistic regression models to investigate the association between HGI and poor outcome. We employed the restricted cubic spline curve to visualize the association between HGI and the risk of poor outcome after EVT.

Results

Among the 403 enrolled patients (median age, 72 years; 63.8% male), a total of 198 (49.1%) patients had poor outcome at 90 days. The restricted cubic spline curve showed that there was a U-shape relationship between HGI and the risk of poor outcome (P for non-linearity < 0.001). After divided patients into three groups based on HGI tertiles, HGI (tertile 1 vs. 2) was significantly associated with poor outcome [odds ratio (OR), 3.84; 95% confidence interval (CI), 2.08-7.22; P < 0.001] and early neurological deterioration (OR, 3.11; 95% CI, 1.55-6.44; P = 0.002) in multivariable analyses. Adding HGI into models improved the discriminative ability for poor outcome (P < 0.001).

Conclusion

In conclusion, our study identified a U-shaped relationship between HGI and poor outcome, with low HGI levels significantly associated with poor outcome after EVT.

Hemoglobin glycation index and cardiovascular outcomes in patients with diabetes and coronary artery disease: insights from a large cohort study

BACKGROUND/OBJECTIVES

The hemoglobin glycation index (HGI) has been demonstrated to serve as a substitute for the individual bias in glycosylated hemoglobin A1c (HbA1c). Our objective was to assess the correlation between HGI and cardiovascular (CV) outcomes in patients with diabetes and coronary artery disease (CAD).

SUBJECTS/METHODS

We sequentially recruited 11921 patients with diabetes and CAD at Fuwai Hospital. The patients were categorized into five groups based on their HGI quintiles, ranging from Q1 to Q5. The primary endpoint was the occurrence of major adverse cardiac events (MACEs), which included CV death and nonfatal myocardial infarction.

RESULTS

During the median 3-year follow-up, 327 (2.7%) MACEs were observed. A U-shaped relationship between HGI and 3-year MACEs was demonstrated by restricted cubic spline (RCS) after multivariable adjustment (nonlinear P = 0.014). The Kaplan-Meier curves demonstrated that the Q2 group had the lowest risk of MACE (P = 0.006). When comparing the HGI Q2 group, multivariable Cox regression models showed that both low (Q1) and high (Q4 or Q5) HGI were linked to a higher risk of MACEs (all P < 0.05). Patients with a low HGI (Q1) had a significantly increased risk of all-cause and CV death, with a 1.70-fold increase in both cases (both P < 0.05).

CONCLUSIONS

In individuals with diabetes and established CAD, HGI levels were found to have a U-shaped relationship with the occurrence of MACEs over a period of three years. Significantly, those with low HGI had an increased risk of CV death.

Glycated haemoglobin index is a new predictor for all-cause mortality and cardiovascular mortality in the adults

Glycosylated haemoglobin index (HGI) has been shown to correlate with the prognosis of metabolic diseases, but the relationship with mortality remains unclear. This study included 18,285 US adults who participated in the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018. During the median follow-up period of 115 months, a total of 2572 all-cause deaths and 671 cardiovascular disease (CVD) deaths occurred. The restricted cubic spline revealed a U-shaped correlation between HGI and all-cause and CVD mortality. After adjusting for all covariates, the optimal inflection point values in all-cause and CVD deaths were 0.17 and 0.02, respectively. In the left side of the inflection point, the risk of all-cause mortality and CVD mortality decreased by approximately 24% (HR 0.76, 95% CI 0.69, 0.84) and 25% (HR 0.75, 95% CI 0.60, 0.96) with the increase in HGI. Conversely, in the right of the inflection point, an increase of 1 unit in the HGI was linked with a 17% (HR 1.17, 95% CI 1.07, 1.27) and 31% (HR 1.31, 95% CI 1.15, 1.49) increase in all-cause and CVD mortality. Our study showed that HGI is an important tool for predicting the risk of all-cause mortality and CVD death in US adults and there is a U-shaped relationship between HGI and mortality.

Risk and mediation analyses of hemoglobin glycation index and survival prognosis in patients with sepsis

An increasing number of studies have reported the close relation of the hemoglobin glycation index (HGI) with metabolism, inflammation, and disease prognosis. However, the prognostic relationship between the HGI and patients with sepsis remains unclear. Thus, this study aimed to analyze the association between the HGI and all-cause mortality in patients with sepsis using data from the MIMIC-IV database. In this study, 2605 patients with sepsis were retrospectively analyzed. The linear regression equation was established by incorporating glycated hemoglobin (HbA1c) and fasting plasma glucose levels. Subsequently, the HGI was calculated based on the difference between the predicted and observed HbA1c levels. Furthermore, the HGI was divided into the following three groups using X-tile software: Q1 (HGI ≤  - 0.50%), Q2 (- 0.49% ≤ HGI ≤ 1.18%), and Q3 (HGI ≥ 1.19%). Kaplan-Meier survival curves were further plotted to analyze the differences in 28-day and 365-day mortality among patients with sepsis patients in these HGI groups. Multivariate corrected Cox proportional risk model and restricted cubic spline (RCS) were used. Lastly, mediation analysis was performed to assess the factors through which HGI affects sepsis prognosis. This study included 2605 patients with sepsis, and the 28-day and 365-day mortality rates were 19.7% and 38.9%, respectively. The Q3 group had the highest mortality risk at 28 days (HR = 2.55, 95% CI: 1.89-3.44, p < 0.001) and 365 days (HR = 1.59, 95% CI: 1.29-1.97, p < 0.001). In the fully adjusted multivariate Cox proportional hazards model, patients in the Q3 group still displayed the highest mortality rates at 28 days (HR = 2.02, 95% CI: 1.45-2.80, p < 0.001) and 365 days (HR = 1.28, 95% CI: 1.08-1.56, p < 0.001). The RCS analysis revealed that HGI was positively associated with adverse clinical outcomes. Finally, the mediation effect analysis demonstrated that the HGI might influence patient survival prognosis via multiple indicators related to the SOFA and SAPS II scores. There was a significant association between HGI and all-cause mortality in patients with sepsis, and patients with higher HGI values had a higher risk of death. Therefore, HGI can be used as a potential indicator to assess the prognostic risk of death in patients with sepsis.

Sex-specific associations between haemoglobin glycation index and the risk of cardiovascular and all-cause mortality in individuals with pre-diabetes and diabetes: A large prospective cohort study

AIM

The aim of this study was to investigate the relationship between the haemoglobin glycation index (HGI), and cardiovascular disease (CVD) and all-cause mortality in adults with pre-diabetes and diabetes.

METHODS

This study included 10 267 adults with pre-diabetes and diabetes from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. Sex-differentiated relationships between HGI and mortality were elucidated using multivariate Cox proportional hazards models, restricted cubic splines and a two-piecewise Cox proportional hazards model.

RESULTS

During the median follow-up time of 103.5 months, a total of 535 CVD deaths and 1918 all-cause deaths were recorded. After multivariate adjustment, in males with pre-diabetes and diabetes, there was a U-shaped relationship between HGI and CVD mortality and all-cause mortality, with threshold points of -0.68 and -0.63, respectively. Before the threshold point, HGI was negatively associated with CVD mortality [hazard ratio (HR) 0.60; 95% confidence interval (CI) 0.41, 0.89] and all-cause mortality (HR 0.56; 95% CI 0.43, 0.74), and after the threshold point, HGI was positively associated with CVD mortality (HR 1.46; 95% CI 1.23, 1.73) and all-cause mortality (HR 1.40; 95% CI 1.23, 1.59). In contrast, HGI had an L-shaped relationship with all-cause mortality and no significant association with CVD mortality in females. To the left of the threshold points, the risk of all-cause mortality decreased (HR 0.50; 95% CI 0.35, 0.71) progressively with increasing HGI.

CONCLUSIONS

In the cohort study, HGI in pre-diabetic and diabetic populations was found to have a U-shaped association with CVD mortality and all-cause mortality in males and an L-shaped association with all-cause mortality only in females. Further prospective and mechanistic studies are warranted.

Risk analysis of the association between different hemoglobin glycation index and poor prognosis in critical patients with coronary heart disease-A study based on the MIMIC-IV database

BACKGROUND

The hemoglobin glycation index (HGI) is the difference between the observed and predicted values of glycosylated hemoglobin (HbA1c), which is closely associated with a variety of poor prognoses. However, there are still no studies on the correlation between HGI and poor prognosis in patients with critical coronary artery disease. The purpose of this study was to analyze the correlation between HGI and all-cause mortality in patients with critical coronary artery disease using the MIMIC-IV database.

METHODS

The HGI was calculated by constructing a linear regression equation between HbA1c and fasting plasma glucose (FPG). A Kaplan‒Meier survival analysis model was constructed based on the HGI quartiles to clarify the differences in all-cause mortality rates between groups, and the log-rank test was used to assess the differences between groups. The hazard ratio (HR) of HGI as a risk factor for outcome events was assessed using the Cox proportional risk model and restricted cubic spline (RCS), with the Q2 group serving as the reference group.

RESULTS

A total of 5260 patients were included in this study. The 30-day mortality rate of the patients was 4.94% and the mortality rate within 365 days was 13.12%. A low HGI was significantly associated with 30-day mortality (HR, 1.96; 95% CI, (1.38, 2.78); P < 0.001) and 365-day mortality (HR, 1.48; 95% CI, (1.19, 1.85); P < 0.001) in patients with critical coronary artery disease in the completely adjusted Cox proportional risk model. In addition, high levels of HGI were associated with 365-day mortality (HR, 1.31; 95% CI, (1.02, 1.69); P < 0.05). RCS analysis revealed a U-shaped relationship between HGI and outcome events. According to the stratified analysis, the interaction test revealed that the correlation between HGI and outcome events remained stable.

CONCLUSION

There was a significant correlation between HGI and all-cause mortality in patients with critical coronary artery disease, particularly in those with low HGI. HGI can be used as a potential indicator for assessing the short- and long-term risk of mortality in such patients.